YES We show the termination of the TRS R: app(app(app(if(),true()),x),y) -> x app(app(app(if(),true()),x),y) -> y app(app(takeWhile(),p),nil()) -> nil() app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) app(app(dropWhile(),p),nil()) -> nil() app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) p2: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))) p3: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(if(),app(p,x)) p4: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(p,x) p5: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(cons(),x),app(app(takeWhile(),p),xs)) p6: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(takeWhile(),p),xs) p7: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) p8: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(if(),app(p,x)),app(app(dropWhile(),p),xs)) p9: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(if(),app(p,x)) p10: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(p,x) p11: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(dropWhile(),p),xs) and R consists of: r1: app(app(app(if(),true()),x),y) -> x r2: app(app(app(if(),true()),x),y) -> y r3: app(app(takeWhile(),p),nil()) -> nil() r4: app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) r5: app(app(dropWhile(),p),nil()) -> nil() r6: app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) The estimated dependency graph contains the following SCCs: {p4, p6, p10, p11} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(p,x) p2: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(dropWhile(),p),xs) p3: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(p,x) p4: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(takeWhile(),p),xs) and R consists of: r1: app(app(app(if(),true()),x),y) -> x r2: app(app(app(if(),true()),x),y) -> y r3: app(app(takeWhile(),p),nil()) -> nil() r4: app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) r5: app(app(dropWhile(),p),nil()) -> nil() r6: app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) The set of usable rules consists of (no rules) Take the reduction pair: lexicographic combination of reduction pairs: 1. lexicographic path order with precedence: precedence: app > dropWhile > app# > takeWhile > cons argument filter: pi(app#) = [1] pi(app) = [2] pi(takeWhile) = [] pi(cons) = [] pi(dropWhile) = [] 2. matrix interpretations: carrier: N^3 order: lexicographic order interpretations: app#_A(x1,x2) = (0,0,0) app_A(x1,x2) = ((0,0,0),(1,0,0),(1,1,0)) x2 + (1,1,1) takeWhile_A() = (1,1,1) cons_A() = (1,1,0) dropWhile_A() = (1,1,1) The next rules are strictly ordered: p1, p3 We remove them from the problem. -- SCC decomposition. Consider the dependency pair problem (P, R), where P consists of p1: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(dropWhile(),p),xs) p2: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(takeWhile(),p),xs) and R consists of: r1: app(app(app(if(),true()),x),y) -> x r2: app(app(app(if(),true()),x),y) -> y r3: app(app(takeWhile(),p),nil()) -> nil() r4: app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) r5: app(app(dropWhile(),p),nil()) -> nil() r6: app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) The estimated dependency graph contains the following SCCs: {p1} {p2} -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: app#(app(dropWhile(),p),app(app(cons(),x),xs)) -> app#(app(dropWhile(),p),xs) and R consists of: r1: app(app(app(if(),true()),x),y) -> x r2: app(app(app(if(),true()),x),y) -> y r3: app(app(takeWhile(),p),nil()) -> nil() r4: app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) r5: app(app(dropWhile(),p),nil()) -> nil() r6: app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) The set of usable rules consists of (no rules) Take the reduction pair: lexicographic combination of reduction pairs: 1. lexicographic path order with precedence: precedence: app# > cons > app > dropWhile argument filter: pi(app#) = [1, 2] pi(app) = [1, 2] pi(dropWhile) = [] pi(cons) = [] 2. matrix interpretations: carrier: N^3 order: lexicographic order interpretations: app#_A(x1,x2) = ((1,0,0),(1,0,0),(1,1,0)) x2 app_A(x1,x2) = ((1,0,0),(0,1,0),(1,1,0)) x1 + ((1,0,0),(1,1,0),(0,0,0)) x2 dropWhile_A() = (0,0,0) cons_A() = (1,1,0) The next rules are strictly ordered: p1 We remove them from the problem. Then no dependency pair remains. -- Reduction pair. Consider the dependency pair problem (P, R), where P consists of p1: app#(app(takeWhile(),p),app(app(cons(),x),xs)) -> app#(app(takeWhile(),p),xs) and R consists of: r1: app(app(app(if(),true()),x),y) -> x r2: app(app(app(if(),true()),x),y) -> y r3: app(app(takeWhile(),p),nil()) -> nil() r4: app(app(takeWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(cons(),x),app(app(takeWhile(),p),xs))),nil()) r5: app(app(dropWhile(),p),nil()) -> nil() r6: app(app(dropWhile(),p),app(app(cons(),x),xs)) -> app(app(app(if(),app(p,x)),app(app(dropWhile(),p),xs)),app(app(cons(),x),xs)) The set of usable rules consists of (no rules) Take the reduction pair: lexicographic combination of reduction pairs: 1. lexicographic path order with precedence: precedence: app# > cons > app > takeWhile argument filter: pi(app#) = [1, 2] pi(app) = [1, 2] pi(takeWhile) = [] pi(cons) = [] 2. matrix interpretations: carrier: N^3 order: lexicographic order interpretations: app#_A(x1,x2) = ((1,0,0),(1,0,0),(1,1,0)) x2 app_A(x1,x2) = ((1,0,0),(0,1,0),(1,1,0)) x1 + ((1,0,0),(1,1,0),(0,0,0)) x2 takeWhile_A() = (0,0,0) cons_A() = (1,1,0) The next rules are strictly ordered: p1 We remove them from the problem. Then no dependency pair remains.